Google Pixel 6
Geekbench ML Score
774
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 11:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Google Pixel 6 |
| Model ID | Google Pixel 6 |
| Motherboard | oriole |
| Governor | performance |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.25 GHz |
| Cluster 3 | 2 Cores @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.28 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
362
67.7 IPS |
|
|
Image Classification (F16)
|
100% |
376
70.3 IPS |
|
|
Image Classification (I8)
|
97% |
830
155.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
427
7.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
419
7.01 IPS |
|
|
Image Segmentation (I8)
|
98% |
682
11.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
752
0.91 IPS |
|
|
Pose Estimation (F16)
|
100% |
743
0.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
3557
4.31 IPS |
|
|
Object Detection (F32)
|
100% |
345
25.8 IPS |
|
|
Object Detection (F16)
|
100% |
350
26.1 IPS |
|
|
Object Detection (I8)
|
61% |
819
61.2 IPS |
|
|
Face Detection (F32)
|
100% |
732
8.70 IPS |
|
|
Face Detection (F16)
|
100% |
751
8.92 IPS |
|
|
Face Detection (I8)
|
86% |
1686
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
743
5.76 IPS |
|
|
Depth Estimation (F16)
|
100% |
748
5.80 IPS |
|
|
Depth Estimation (I8)
|
95% |
1844
14.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1391
1.83 IPS |
|
|
Style Transfer (F16)
|
100% |
1351
1.78 IPS |
|
|
Style Transfer (I8)
|
98% |
3016
3.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
570
20.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
535
19.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1997
71.3 IPS |
|
|
Text Classification (F32)
|
100% |
517
743.4 IPS |
|
|
Text Classification (F16)
|
100% |
504
725.0 IPS |
|
|
Text Classification (I8)
|
92% |
538
773.7 IPS |
|
|
Machine Translation (F32)
|
100% |
913
16.8 IPS |
|
|
Machine Translation (F16)
|
100% |
891
16.4 IPS |
|
|
Machine Translation (I8)
|
64% |
470
8.64 IPS |
